Computational methods for signal processing provide foundation technologies for many different types of systems and services, including systems and services related to recording, transmission, and rendering of signals that encode images and graphics, including photographic images, video signals, and other such signals. Over the years, many different types of image-enhancement functionalities have been devised and implemented, including computational routines and/or logic circuits that implement sharpening, local and global contrast enhancement, denoising, and other such image-enhancement functionalities.
Unfortunately, in many cases, these image-enhancement techniques are separately applied in order to carry out a comprehensive, multifaceted image enhancement, leading to computational inefficiency. Application of any of various image-enhancement techniques may often produce uneven results across an image, and may lead to introduction of perceptible anomalies and artifacts that propagate through application of a series of separate image-enhancement techniques. In many cases, one type of enhancement may result in degradation of one or more characteristics of an image to which enhancement is not directed, so that comprehensive image-enhancement methods may comprise a series of tradeoffs and compromises. For all of these reasons, designers, developers, vendors, and users of image-enhancement software, image-enhancement-related logic circuits, image-enhancement-related systems and devices, and a large number of different types of devices that include image-enhancement functionality, have all recognized a need to continue to devise and develop improved computational methods for enhancing two-dimensional images and other signals, including signals that encode video frames, graphics, and other visually displayed information.